A desktop application built with CustomTkinter that analyzes video files to identify potential ad break points by detecting sequences of black frames and silent audio sections, and finding where these two types of intervals overlap.

Features

• Black Frame Detection: Scans video frames to find sequences where the average pixel intensity falls below a configurable threshold.
• Silent Audio Detection: Analyzes the audio track to find sections where the audio level stays below a configurable silence threshold for a minimum duration (using PyAudioAnalysis).
• Overlap Identification: Finds intervals where detected black frame sequences and silent audio sections coincide.
• Customizable Parameters: Allows users to set the minimum duration for black/silent sequences and the blackness/silence thresholds via the GUI.
• CSV Export: Exports the detected black frame sequences, silent sections, and overlapping intervals to a single, structured CSV file.
• User-Friendly GUI: Provides a simple interface for selecting video files, configuring parameters, running the analysis, and viewing results and output.
• Background Processing: Runs the analysis in a separate thread to keep the GUI responsive.

Dependencies

The application relies on the following Python libraries:

• customtkinter: For the modern graphical user interface.
• Pillow (PIL): For image handling (used by CustomTkinter).
• opencv-python (cv2): For video frame processing.
• numpy: For numerical operations (used by OpenCV and other libraries).
• pyAudioAnalysis: For silent audio detection.
• scipy: A scientific computing library (dependency of PyAudioAnalysis).
• scikit-learn (sklearn): A machine learning library (dependency of PyAudioAnalysis).
• matplotlib: A plotting library (dependency of PyAudioAnalysis, even if plots aren't directly shown).
• pydub: (Used in the alternative ffmpeg/pydub version) For audio manipulation and silence detection.
• ffmpeg-python: (Used in the alternative ffmpeg/pydub version) A Python wrapper for FFmpeg.

External Dependency:

FFmpeg: The application requires the external ffmpeg and ffprobe executables to be installed on the system for audio analysis (used by pyAudioAnalysis or ffmpeg-python). The application includes a runtime check and warning if ffmpeg is not found.